Fatou Jaiteh1,2,3*
Joan Muela Ribera4
Yoriko Masunaga2,3
Joseph Okebe1,5
Umberto D'Alessandro1,6
Julie Balen7Jane Achan1,5Rene Gerrets3
Koen Peeters Grietens2,4,8- 1Medical Research Council Unit the Gambia at the London School of Hygiene and Tropical Medicine, Banjul, Gambia
- 2Medical Anthropology Unit, Institute of Tropical Medicine, Antwerp, Belgium
- 3Faculty of Social and Behavioural Sciences, Amsterdam Institute of Social Science Research, Amsterdam, Netherlands
- 4PASS Suisse, Neuchâtel, Switzerland
- 5Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- 6London School of Hygiene and Tropical Medicine, London, United Kingdom
- 7School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, United Kingdom
- 8School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
With significant declines in malaria, infections are increasingly clustered in households, or groups of households where malaria transmission is higher than in surrounding household/villages. To decrease transmission in such cases, reactive interventions target household members of clinical malaria cases, with the intervention unit (e.g., the “household/s”) derived from an epidemiological and operational perspective. A lack of unanimity regarding the spatial range of the intervention unit calls for greater importance to be placed on social context in conceptualizing the appropriate unit. A novel malaria elimination strategy based on reactive treatment was recently evaluated by a cluster randomized trial in a low transmission setting in The Gambia. Transdisciplinary research was used to assess and improve the effectiveness of the intervention which consisted, among others, of reflecting on whether the household was the most adequate unit of analysis. The intervention was piloted on the smallest treatment unit possible and was further adapted following a better understanding of the social and epidemiological context. Intervention units defined according to (i) shared sleeping spaces and (ii) household membership, showed substantial limitations as it was not possible to define them clearly and they were extremely variable within the study setting. Incorporating local definitions and community preference in the trial design led to the appropriate intervention unit—the compound—defined as an enclosed space containing one or several households belonging to the same extended patrilineal family. Our study demonstrates the appropriateness of using transdisciplinary research for investigating alternative intervention units that are better tailored to reactive treatment approaches.
Introduction
Following a significant decline in malaria transmission, infections become increasingly clustered in “households or groups of households which maintain higher levels of transmission” than the rest of the population (1, 2). In these clusters, both incidence of clinical malaria and prevalence of infection would be higher than in the surrounding areas (3, 4). Targeting geographical clusters of both clinical and asymptomatic infections could therefore decrease the human reservoir of infection and thus further reduce malaria transmission (5–9).
In low-transmission settings, progress toward malaria elimination may be achieved by surveillance-based approaches, such as reactive interventions (3, 8). Similar to contact tracing for infectious diseases such as Ebola, tuberculosis, and coronavirus, reactive interventions are triggered when an “index clinical case” is diagnosed at a health facility, initiating a visit by health workers to the symptomatic case's household and/or surrounding households for the screening and/or (presumptive) treatment of family members and neighbors (7). Given the centrality of the “household/s” in the approaches, its conceptualization remains intricately tied to the unit of the intervention (10, 11). The household constitutes the central unit of analysis for most surveys [such as the health and demographic surveillance systems (HDSS)] and types of interventions but is seldom critically examined, reflecting the dominant approach in reactive interventions and more generally in demography (10, 12). Social diversity in the composition of the household (13, 14), i.e., how it is socio-culturally, politically and economically defined/constituted and the implications of such definition for its analysis) are often not considered a priori.
Reactive interventions such as reactive case detection (RACD) has been widely implemented across various epidemiological settings, including those that recently attained or are closer to malaria elimination (3, 8). A key issue influencing the efficiency of the RACD is the spatial range of the unit of intervention, frequently referred to as the “radius of the intervention.” Typically, for RACD, everybody living in the index clinical case household is screened and treated if positive or treated regardless of their infection status. However, the spatial range and the extent to which other households are considered for screening or treatment varies (3, 15–18). Determining this geographical parameter largely follows an epidemiological and operational perspective (3, 15, 19). Epidemiological factors are defined according to local transmission, vector species, environment which determine the geographical boundaries used to identify those at risk or vulnerable to infection (20–23). The operational factors pragmatically consider the ability of the local health systems to implement RACD in terms of availability of resources (funding, human resources) (3, 15, 18, 24). The latest Global Technical Strategy (2016–2030) for malaria, which reinforces calls for eradication by setting out the vision for a malaria free world, describes the spatial range for RACD approaches as the most efficient, sensitive, and feasible radius for testing around the index malaria case, depending on the epidemiology and the local health system (24). This perspective allows for the adaptation of the intervention unit according to the local setting in terms of disease transmission and health system factors but abstracts it from the social context. Protocols and research for case investigations in RACD vary widely, with often limited evidence for, or justification of, the decisions guiding the geographic scope of the intervention (3, 15, 19). Previous research has shown that social variability, i.e., migration, livelihoods, housing structure, residence, and sleeping patterns, within which they occur play a key part on the effectiveness of biomedical interventions (25–27). Nonetheless, to date, there are no studies that have explored how social context influence RACD approaches; community involvement in defining what is the appropriate targeted intervention unit has been rarely investigated. Given the diverse and complex pathways which affect malaria risk and disease transmission, addressing this gap remains crucial toward a better understanding of the appropriate intervention unit for RACD approaches.
The Study Protocol and Related Assumptions
As researchers, we were involved in a novel approach where transdisciplinary research was used to assess and improve the effectiveness of RACD to target asymptomatic malaria-infected individuals (secondary cases), part of which consisted of establishing whether the household should be the unit of intervention as initially proposed in the study protocol. The transdisciplinary study conducted in The Gambia was centered around a cluster randomized trial (CRT), reactive household-based, self-administered treatment (RHOST) (ClinicalTrials.gov, NCT02878200, 25/08/2016) evaluating a new RACD approach that combined: (i) the passive detection of clinical malaria cases; (ii) systematic treatment with dihydroartemisinin-piperaquine (DHAP) of all household members sharing the same sleeping area with the index clinical case, without screening for infection; and (iii) an active community participation strategy involving patients, their households and other community actors as stakeholders in the intervention strategy (28). The trial was planned over two transmission seasons. In the first season (preparatory phase), 17 intervention and 17 control villages were identified and approaches to integrate the intervention into the communities and the health system were tested and adapted through formative research. During this process, trial implementation concerns were identified and solutions co-developed with relevant stakeholders, including community members, health service providers and policy makers. According to the original design, a clinical malaria case (index case) from an intervention village, after being diagnosed at the local health facilities or by village health workers, will be given a sufficient amount of DHAP to treat all members of their household. One key challenge of the approach was the definition of the intervention unit (i.e., treatment unit for epidemiological impact), which lies with the conceptualization of the household.
Maintaining the current dominant scientific paradigm of standardized households may shadow alternative contextualized solutions which addresses the realities of the concept of the household (29, 30). To date, household definitions remain influenced by the United Nations (UN) household guidelines for census enumerations based on the three main criteria of (i) residence (i.e., living together/sleeping under the same roof); (ii) housekeeping (i.e., pooling of resources), and (iii) provision of food (i.e., eating from the same pot). For post-colonial states like The Gambia, the adoption of the UN term of “household” and its corresponding guidelines for their national statistical systems became a measure of their transformation into “modern states” and of the attainment of their development goals as evaluated by the international community (31). The UN approach has been criticized for being Eurocentric as its premise is built around the organization of small nuclear families which often differs from the dynamic living arrangements in much of sub-Saharan Africa (10, 31).
To address fundamental tensions that arise between the standardized household concept as proposed by the UN and contextually variable local residence patterns and social organization, countries slightly modified the UN definition (31). For instance, the 2013 Gambian population and housing census defines the household “as a person or group of persons who live together in the same house or compound, share the same house-keeping arrangements and are catered for as one. It might be worth noting that members of a household are not necessarily related by blood or marriage as the case of maids in some instances” (32). The definition maintains focus on the UN criteria of housekeeping and provision of food, with slight “adaptation” of residence to the national context. Nonetheless, for comparability purposes, the national definition remains problematic since it also implies a standardized unit, which in practice, remains flexible. Comparisons for the purpose of research could be made with standardized surveys which in contrast to national censuses collects more in-depth data at the household level. For instance, the HDSS set up in the study area, collects data on demographic and population-based health indicators at the household level to support and inform clinical studies (33). The HDSS defines the household as “a person or group of persons living in the same house or compound, sharing the same cooking arrangements” (33). Although the definition also accounts for residency, it does not explicitly state the role of kinship relations in defining household membership.
Household variability include social rules governing marriage and family, kin and non-kin obligations and other political and economic aspects, and may manifest to a significant degree within the context of intra-household relations (10, 12, 34, 35). Its definition can rarely be standardized and for its appropriate application in research, it may be more useful to consider the social dynamics affecting specific aspects related to the goals of a specific intervention (34). Our study therefore aimed to identify the relevant social contextual factors for defining an appropriate intervention unit for the RACD approach.
Methods
Study Setting and Population
This transdisciplinary study was carried out during the preparatory phase of the trial in the North Bank region of The Gambia. Study villages were mainly populated by Fula, Mandinka, and Wolof ethno-linguistic groups, with a minority identifying themselves as Bambaras, Turkas, and Tilibonkas who migrated from neighboring Mali, Guinea, and Burkina Faso, respectively. The population is mainly Muslim. Most of the villagers were engaged in cash-crop and subsistence farming and, to a lesser extent, herding for livelihood. Peanuts are the main cash-crop while rice, maize, beans, and vegetables are grown as subsistence crops. Migration into the area is common during the rainy season when demand for labor in agricultural practices is high. The pursuit of socioeconomic advancements has contributed to young men migrating out of the area, mainly to Europe, influencing the local economic and social life. The economy of a significant number of local families are supplemented by remittances received from relatives abroad.
Malaria Transmission
The Gambia is one of seven countries in West Africa that has achieved significant progress toward malaria elimination (36). The progress has been attributed to the scale-up of standard control measures, that include case management with artemisinin-based combination therapy (ACT) and Long-Lasting Insecticide Treated Bed nets (LLINs) (37). Nevertheless, malaria transmission remains spatially heterogenous, with two major strata, low transmission in western and central Gambia and moderate transmission in eastern Gambia. The study setting was considered a low transmission area, with malaria prevalence of <5% (36). Plasmodium falciparum is the main malaria species in the area.
Study Design
As part of the formative research, a qualitative study based on ethnographic methods was carried out in continuous dialogue with field epidemiological investigations. The research strategy used an emergent theory design (38) wherein new insights from on-going data collection aimed to nurture existing theory in the two disciplines involved. The research team consisted of social scientists and fieldworkers. All social scientists had previous research experience in the region. The fieldworkers, also acting as translators, had received training and were experienced in social science research. The research was carried out in collaboration with a larger inter-disciplinary team of epidemiologists, health system, and health economics researchers.
Data Collection
Fieldwork conducted between March–December 2016 facilitated data collection through in-depth interviews (n = 88), participant observation [including informal conversations (n = 9)], participatory group discussions (n = 10), cases studies (n = 10) and review of trial reports. Data from the different methods were triangulated to confirm, challenge and deepen the validity of the conclusions that either component might yield alone.
Sampling
A purposive sample of study participants was included and access to the informants was facilitated through snowball sampling. The latter increased confidentiality and trust with respondents and further improved reliability in the collected data. Interviews were carried out in English and translated into the language of the respondent by trained fieldworkers. All responses were translated back in English to the researchers. Interviews were all recorded and transcribed verbatim by the translators. Additionally, fieldnotes were written during interviews by the researchers or immediately after the interviews.
Data Analysis
An iterative process of analysis was performed concurrently with data collection. Investigators conducted preliminary analysis together whilst in the field and these findings were translated into question guides for follow-up interviews. Final transcripts and fieldnotes were systemized and analyzed thematically in NVivo 11 Qualitative Data Analysis software (QSR International Pty Ltd. Cardigan UK).
Ethics
Approval, for the study, including oral consent, was obtained from the Gambia Government/MRC Joint Ethics Committee and by the Institutional Review Board of the Institute of Tropical Medicine, Antwerp, Belgium. The interviewers followed the Code of Ethics of the American Anthropological Association. All interviewees were informed before the interview about the topic and types of questions and their right to decline participation, to interrupt or withdraw from the research. Oral consent was sought before each interview and was documented by the interviewer. Oral consents were preferred as the risk to the participant was minimal and the act of signing one's name on a document could create mistrust since it is not customary practice within the local communities. Interviewees' confidentiality was assured by assigning unique identifiers to the collected forms.
Results
We present how the RACD intervention unit was operationalized by outlining the different options considered during the trial implementation. The first step was a pilot of the intervention at the smallest treatment unit possible and then, adapting the strategy based on an emergent understanding of the social and epidemiological context.
Operationalizing the RACD Intervention Unit
The Sleeping Space as Treatment Unit
Initially, the “sleeping space” was chosen as the smallest possible treatment unit, being potentially the most feasible. Treatment based on sleeping spaces was operationalized as targeting “people sleeping in the same room with a clinical index case.” Targeting the physical unit where people sleep was considered relevant based on (i) epidemiological evidence of malaria clustering around a clinical case (3, 4); (ii) the consideration that malaria treatment distribution was more feasible when limited to a smaller number of persons, and (iii) the implicit assumption that sleeping areas and who sleeps where was easily determined and stable. The following issues in identifying individuals eligible for reactive treatment based on targeted “sleeping areas” were the most common.
Unclear Unit Definition
Challenges with defining the spatial unit of the intervention were related to (i) difficulties in defining sleeping spaces within a room vs. the house; and (ii) entomological evidence on the influence of housing structures on malaria transmission (39–41). In the study area, the common housing structures were: (i) traditional single-room mud houses with thatched roofs and open eaves; and (ii) multi-room cement line houses with corrugated roofs. In the former, there was a single enclosed space which served several functions, including for sleeping. In the latter, multiple adjacent rooms often separated by walls that did not extend to the roof served as sleeping areas. These different housing structures co-existed in intervention villages, suggesting that our initial definition of a “sleeping area” was heterogeneous and not very practical for implementing the intervention.
Flexibility of Sleeping Patterns and Intra-Household Mobility
Sleeping patterns within rooms were very heterogenous and flexible. Sleeping patterns were largely based on social rules on kinship and marriage (42–44), wherein the simplest model was: “the husband sleeps with his male children in one room, while his wife sleeps with the mother-in law and female children in another room.” However, in a compound with several houses, each of them was occupied by an adult male and his family [wife/s and child(ren)]. The sleeping arrangements for children depended on their age and gender, with children under 5 years sharing a sleeping room with their mother. For older children, the females shared a room with their mothers while the males shared with their father or had a separate room (i.e., so-called boy's rooms). In most polygamous marriages (45), the husband would have an individual room where wives took turns to sleep. Although these arrangements present a systematic pattern, changes to the location and persons staying in these rooms were frequent.
These changes were mainly for social reasons such as when children moved from their mother's to grandmothers' room due to illness or to accommodate visitors (42). Same-gender sleeping arrangements were the norm for adults.
“If I have stranger (guest) who I know, you know it can be my friend, then I sleep with them in my room, but if it is a child, he/she sleeps with the children. If the bed is small for them, they spread down to sleep while the stranger (guest) will sleep on the bed.” (Household head, in-depth interview)
Based on these arrangements, children—mostly boys—were most likely to move across sleeping places in the house. Changes in sleeping locations were also affected by the season; household members slept outdoors due to hot weather. Such intra-household mobility and changes in sleeping locations occasionally affected the identification of participants eligible for treatment. For example, in an index-case household, some people who normally slept in the same room with the index case but temporarily moved to another room were missed for treatment based on the trial criteria of locating persons based on fixed sleeping spaces. Considering these challenges highlighted for treating “people sleeping in the same room with a clinical index case,” from the trial's perspective, the next logical step to consider as treatment unit was “all members of the household of the clinical index case.”
The Household as Treatment Unit
Targeting all household members living with the clinical index case assumed that (i) the household was clearly defined which was; (ii) ideal for scaling up the intervention as people could easily name all persons living in their household. Our ethnographic findings showed that the local household was largely understood within the context of social organization and centered on patrilineal kinship relations and virilocal patterns of residence (i.e., women leaving to reside in the village of the father of their husbands) (45–47). Gender roles provided men a predominant position within the family, defining them as household heads, and considered as the leaders of the therapy management group, i.e., individuals who took charge of therapy management with or on behalf of the sufferer (48–50). The household head and other senior family members could identify household members, including at least two generations of extended families (e.g., mother, brother, their wives and children). This group of people were described as normally living together and eating from the same cooking pot (i.e., common cooking arrangement) (10). The local definition, however, had a limited interpretation that moved away from the initial trial approach of capturing all persons living in the same household with a clinical index case. Its implication for the treatment unit became particularly relevant when considering that seasonal migration during the rainy (malaria transmission) season was a common activity in the area.
Seasonality and household composition
In most communities, rural households need additional labor for peanut farming (50). Therefore, the farming period accounted for short-term migration of seasonal workers from neighboring villages or other countries. Two categories of seasonal workers were observed which affected household compositions and further gave meaning to de-facto membership (actually living in or considered to be a permanent member of the household). The first category of workers were the members of the household who returned temporarily to support the family on the farms. These were mostly persons that had moved for economic reasons to urban areas within the country or elsewhere in Africa (45, 51). Although mostly absent during the year, migrant sons were regarded as members of the household due to the kinship relations, and their financial contribution to the household through remittances. During the time of their visit, the migrant sons, if unmarried would sleep in the father's room or boy's room, and if married slept in their own house within the compound.
The other category of short-term migrants were hired workers (45, 52) also referred to as surga or mbedan. Based on the availability of land and financial strength, household heads hired seasonal workers with different payment agreements, i.e., the surga received a piece of land they could cultivate while working in the owner's fields, and the mbedan worked for a pre-stablished amount of cash. These surgas and/or mbendans often shared the household accommodation either with the older males or in separate rooms.
“You know this is the same compound if I catch a surga and my brother happens to catch another surga we look for a separate house for them to occupy in the compound.” (Adult man, farmer, in-depth interview)
Our findings reveal that the presence of seasonal workers during the agricultural period was common in the study villages. Nevertheless, when asked to list the members of their household, the household head does not mention short-term migrants unless specifically enquired for (35). The findings resonate with previous literature, which show that households are largely made up of individuals related by blood or marriage (11, 13, 52). These cultural explanations give insights into migrants' integration within households and compounds, including implications for the enumeration of those targeted for treatment. In the context of declining malaria, when the majority of imported cases are often related to seasonal and long-term migrants (53), it is essential to question whether a targeted treatment unit based on residency criteria alone was an efficient approach.
The Compound as Treatment Unit
Beyond the household, the compound was relevant as a socio-spatial unit for the intervention. Epidemiologically, it was a larger spatial unit with clusters of people with similar exposure to mosquito bites and treatment-seeking behavior (28, 54). The compound also accounted for the social structures and local residence patterns mostly based on kinship and marriage relations (47, 55). Compounds within the village were typically characterized as an enclosed space of one or several households belonging to the same extended patrilineal family (47). Informants described several variations of the basic structure of social organization depending on its size (47). Nonetheless, the compound was clearly identified as the largest unit of residence, therapy and production unit in which authority was exercised (55) and accounted for all household members.
Operationally, treatment at the level of the compound seemed a much clearer target in terms of the potential for scaling up. Compounds addressed the issue of intra-household mobility in sleeping arrangements but also provided stability in allocations as people rarely slept out of their compounds. Nevertheless “treating all compound members of a clinical index case” was operationally complex due to the larger number of persons to be treated, on average 15.6 persons/per compound.
Malaria risk perception
Our key community group discussions and interviews revealed further limitations with restricting treatment to those sharing sleeping spaces or living in the same household with a clinical index case. Community responses toward defining the treatment unit were varied and related to their perception of malaria risk.
“If my household takes the medicine, we are still not fully protected because we still mingle with other household members (eat together, share utensils), chat outside late at night with other villagers.” (Household head, in-depth interview)
Informants expressed that people, particularly young men, from different households (from the same compound, from the same village and even from different villages) stayed outdoors until late at night (several participants specified “until 1 a.m.”). They pointed out that the risk of contracting and transmitting malaria went beyond their household, to include the compound and the village. In case of households, most informants that received treatment considered themselves and others (who they slept together with and took the medicine) within their household as protected from malaria. Informants explicitly mentioned that although all those who slept together with the malaria patient were protected, other untreated persons within the same household and compound, other surrounding compound and the village at large remained at risk of malaria.
“Everyone in the compound should be treated, because if treatment is given to those who sleep together whilst they still stay with others that don't have treatment, it means they are still not fully protected.” (Caretaker of index case, in-depth interview)
Some respondents insisted that it would be a good intervention to provide treatment at the compound or even at the village level, for general prevention for all. These expressions for mass treatment beyond the household and compound unit by the community members were often made in reference to previous mass drug administration programs for malaria implemented in the area (26, 56, 57).
Discussion
Our research aimed to identify relevant social contextual factors for defining the appropriate intervention unit (i.e., treatment unit) for RACD—which departed from the commonly-used household as the key analytic unit. Our findings on the rural Gambian household reinforces the notion that there is no one-size-fits-all definition (10, 13, 34, 55), and highlights tensions between local realities and standardized ideals crucial to RACD and more generally epidemiological approaches. The findings confirm that for interventions focused on the household level, on which policy decisions are frequently based, relevant social dynamics such as living arrangements must be well-understood (31).
Within the study setting, variation in sleeping patterns and household membership reflecting local realties were commonplace, presenting a mismatch with universalist assumptions. As observed in other sub-Saharan African settings, flexibility in sleeping patterns is often necessary to accommodate guests whilst also contributing to the early childhood socialization (58–60). The observed variations in sleeping patterns contributed to the complexity of identifying people for the intervention based on where they slept. Further contributing toward this complexity were local understandings about who is a member of the household. The exclusion of non-kin, non-blood relations such as seasonal workers in the local household definition was explicit in our data. On the other hand, children who left home, but maintained financial contribution and collaborated in productive agricultural work remained included. This highlights the importance of the phrasing of questions surrounding the household and the compounds in surveys and raises questions about accuracy of demographic and socio-economic data given the high migration levels of Gambian men (61).
Given the fluidity surrounding the concept of the household, in practice, the compound was highlighted as a better-defined treatment unit, because it signified (i) a clear spatial residential unit which accommodated most household members, (ii) a productivity unit which fostered cooperation and solidarity amongst household members, and (iii) included a therapy management group to enable the distribution of treatment. Previous research shows the relevance of the compound for adequately capturing social dynamics, including residency patterns which remains crucial for health interventions (33, 47). The corresponding advocacy by some community members for mass biomedical treatment at village level should not be ignored. Such advocacy creates tension with the basic premise of this intervention as the RACD approach for the trial was conceptualized based on the call for more targeted approach for malaria elimination (9). However, their preference could be understood within the backdrop of community trust with biomedical interventions and the availability of vital therapeutic opportunities (62). Before the RACD intervention, a most recent MDA for malaria was implemented in the area by the Medical Research Council, the Gambia (MRCG) (26). Moreover, this research institute was perceived as an alternative health provider within an extremely limited health system. The relationship between the MRCG and communities in the Gambia and its implications for trust in research has been extensively discussed (26, 62–66).
Our findings highlight that even within an environment which fosters trust in biomedical interventions and wherein communities are engaged, tensions can still exist between biomedical rationale of implementing an intervention (i.e., designing a more targeted contextualized intervention for impact on malaria transmission) with community interests (i.e., in terms of addressing their perception of malaria risk to beyond defined boundaries). Addressing this issue, requires the continuous use of co-creative systemic research approaches (29), which acknowledges that community members and researchers both bring valuable insights during the research process, and that knowledge ought to be generated collaboratively (67). Community members have detailed knowledge on their contextual realities that shape their risk perceptions, whilst researchers contribute toward the research methods and methodologies. This complementary approach gives further insights on the avenues for building bridges between the primary aims of research with community concerns on its relevance.
Attempts to standardize and pre-define a complex, fluid and essentially subjective concept of the household has implications for the way household composition and residence are understood (68). Variability in household definitions have been accounted for during survey designs, wherein the tools are attuned to capture the diverse realities whilst still maintaining standardization for comparability purposes (10, 68). Moreover, it is acknowledged that if contextualized household definitions are clearly stated, including its implications, this could counter misunderstandings and therefore lead to its more informed analysis (31, 34, 55). Such a perspective can also help us understand why it is important to consider and address social variability in interventions such as RACD-type approaches. This RACD intervention considers the unique transmission patterns of our study setting, similar to some parts of sub-Saharan Africa were malaria clustering occurs mainly within local villages or compounds (1, 2).
Conclusion
For this study, social variability at the household level was addressed through a transdisciplinary approach which considered and understood what works for the people and worked for the project. This was facilitated by asking the relevant questions and using emerging findings from ethnography and community participatory discussions to improve epidemiological outcomes and address epidemiological concerns for implementation as they emerge. Our findings show that, with this approach, RACD intervention units, can be appropriately tailored to local realities.
Data Availability Statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics Statement
The studies involving human participants were reviewed and approved by approval, for the study, including oral consent, was obtained from the Gambia Government/MRC Joint Ethics Committee and by the Institutional Review Board of the Institute of Tropical Medicine, Antwerp, Belgium. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
Author Contributions
FJ, JR, and KP conceptualized the study. FJ and JR designed the experiments and mainly collected and analyzed the data. FJ wrote the manuscript and KP contributed as well. YM, JO, UD'A, JA, JB, RG, JR, and KP edited and reviewed the manuscript. All main authors read and approved the final manuscript.
Funding
This study was jointly funded under the Global Health Trials Scheme by the Medical Research Council (United Kingdom), the Department for International Development (DFID). This UK-funded award was part of the European and Developing Countries Clinical Trials Partnership (EDCTP2) programme supported by the European Union.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments
We would like to thank our fieldwork team for their hard work and dedication. We are most grateful to our study participants and communities for their time and effort in participating in the study.
References
1. Sturrock HJW, Hsiang MS, Cohen JM, Smith DL, Greenhouse B, Bousema T, et al. Targeting asymptomatic malaria infections: active surveillance in control and elimination. PLoS Med. (2013) 10:e1001467. doi: 10.1371/journal.pmed.1001467
2. Bousema T, Okell L, Felger I, Drakeley C. Asymptomatic malaria infections: detectability, transmissibility and public health relevance. Nat Rev Microbiol. (2014) 12:833–40. doi: 10.1038/nrmicro3364
3. Sturrock HJW, Novotny JM, Kunene S, Dlamini S, Zulu Z, Cohen JM, et al. Reactive case detection for malaria elimination: real-life experience from an ongoing program in Swaziland. PLoS ONE. (2013) 8:e63830. doi: 10.1371/journal.pone.0063830
4. Mosha JF, Sturrock HJW, Greenwood B, Sutherland CJ, Gadalla NB, Atwal S, et al. Hot spot or not: a comparison of spatial statistical methods to predict prospective malaria infections. Malar J. (2014) 13:53. doi: 10.1186/1475-2875-13-53
5. Bousema T, Griffin JT, Sauerwein RW, Smith DL, Churcher TS, Takken W, et al. Hitting hotspots: spatial targeting of malaria for control and elimination. PLoS Med. (2012) 91:e1001165. doi: 10.1371/journal.pmed.1001165
6. Smith JL, Auala J, Tambo M, Haindongo E, Katokele S, Uusiku P, et al. Spatial clustering of patent and sub-patent malaria infections in northern Namibia: implications for surveillance and response strategies for elimination. PLoS ONE. (2017) 12:e0180845. doi: 10.1371/journal.pone.0180845
7. Stresman G, Bousema T, Cook J. Malaria hotspots: is there epidemiological evidence for fine-scale spatial targeting of interventions? Trends Parasitol. (2019) 35:822–34. doi: 10.1016/j.pt.2019.07.013
8. Reiker T, Chitnis N, Smith T. Modelling reactive case detection strategies for interrupting transmission of Plasmodium falciparum malaria. Malar J. (2019) 18:259. doi: 10.1186/s12936-019-2893-9
9. World Health Organization. A Framework for Malaria Elimination. (2017). Available online at: https://www.who.int/malaria/publications/atoz/9789241511988/en/ (accessed March 16, 2017).
10. Randall S, Coast E, Leone T. Cultural constructions of the concept of household in sample surveys. Population Stud. (2011) 65:217–29. doi: 10.1080/00324728.2011.576768
11. Randall S. Family and household in development. Int Encycl Anthropol. (2018). doi: 10.1002/9781118924396.wbiea1546
12. Biruk C. Cooking Data Culture and Politics in an African Research World. Durham, NC; London: Duke University Press (2018).
13. Netting R, Wilk R, Arnould EJ. Households: Comparative and Historical Studies of the Domestic Group. Berkeley, CA; Los Angeles, LA; London: University of California Press (1984).
14. Gödecke T, Waibel H. Does the underlying definition of household impair programme targeting? J Dev Eff. (2016) 8:1–18. doi: 10.1080/19439342.2015.1079793
15. Littrell M, Sow GD, Ngom A, Ba M, Mboup BM, Dieye Y, et al. Case investigation and reactive case detection for malaria elimination. Malar J. (2013) 12:331. doi: 10.1186/1475-2875-12-331
16. Searle KM, Hamapumbu H, Lubinda J, Shields TM, Pinchoff J, Kobayashi T, et al. Evaluation of the operational challenges in implementing reactive screen-and-treat and implications of reactive case detection strategies for malaria elimination in a region of low transmission in southern Zambia. Malar J. (2016) 15:412. doi: 10.1186/s12936-016-1460-x
17. Yukich J, Bennett A, Yukich R, Stuck L, Hamainza B, Silumbe K, et al. Estimation of malaria parasite reservoir coverage using reactive case detection and active community fever screening from census data with rapid diagnostic tests in southern Zambia: a re-sampling approach. Malar J. (2017) 16:317. doi: 10.1186/s12936-017-1962-1
18. Van Eijk AM, Ramanathapuram L, Sutton PL, Kanagaraj D, Sri Lakshmi Priya G, Ravishankaran S, et al. What is the value of reactive case detection in malaria control? A case-study in India and a systematic review. Malar J. (2016) 15:67. doi: 10.1186/s12936-016-1120-1
19. Parker DM, Landier J, Von Seidlein L, Dondorp A, White L, Hanboonkunupakarn B, et al. Limitations of malaria reactive case detection in an area of low and unstable transmission on the Myanmar-Thailand border. Malar J. (2016) 15:571. doi: 10.1186/s12936-016-1631-9
20. Gerardin J, Bever CA, Bridenbecker D, Hamainza B, Silumbe K, Miller JM, et al. Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study. Malar J. (2017) 16:248. doi: 10.1186/s12936-017-1903-z
21. Hsiang MS, Ntuku H, Roberts KW, Dufour MSK, Whittemore B, Tambo M, et al. Effectiveness of reactive focal mass drug administration and reactive focal vector control to reduce malaria transmission in the low malaria-endemic setting of Namibia: a cluster-randomised controlled, open-label, two-by-two factorial design trial. Lancet. (2020) 395. doi: 10.2139/ssrn.3454698
22. Aidoo EK, Afrane YA, Machani MG, Chebore W, Lawson BW, Atieli H, et al. Reactive case detection of Plasmodium falciparum in western Kenya highlands: effective in identifying additional cases, yet limited effect on transmission. Malar J. (2018) 17:111. doi: 10.1186/s12936-018-2260-2
23. Bhondoekhan FRP, Searle KM, Hamapumbu H, Lubinda M, Matoba J, Musonda M, et al. Improving the efficiency of reactive case detection for malaria elimination in southern Zambia: a cross - sectional study. Malar J. (2020) 19:175. doi: 10.1186/s12936-020-03245-1
24. World Health Organization. Global Technical Strategy and Targets for Malaria 2016 – 2030. (2016). Available online at: https://www.who.int/malaria/areas/global_technical_strategy/en/ (accessed January 5, 2015).
25. Chandler CIR, Beisel U. The anthropology of malaria: locating the social.medical anthropology. Med Anthropol. (2017) 36:411–21. doi: 10.1080/01459740.2017.1306858
26. Dierickx S, Gryseels C, Mwesigwa J, O'Neill S, Bannister-Tyrell M, Ronse M, et al. Factors associated with non-participation and non-adherence in directly observed mass drug administration for malaria in the Gambia. PLoS ONE. (2016) 11:e0148627. doi: 10.1371/journal.pone.0148627
27. Gryseels C, Durnez L, Gerrets R, Uk S, Suon S, Set S, et al. Re-imagining malaria: heterogeneity of human and mosquito behaviour in relation to residual malaria transmission in Cambodia. Malar J. (2015) 14:165. doi: 10.1186/s12936-015-0689-0
28. Okebe J, Ribera JM, Balen J, Jaiteh F, Masunaga Y, Nwakanma D, et al. Reactive community-based self-administered treatment against residual malaria transmission: study protocol for a randomized controlled trial. Trials. (2018) 19:126. doi: 10.1186/s13063-018-2506-x
29. Peeters Grietens K, Gryseels C, Verschraegen G. Misdirection in the margins of malaria elimination methods. Crit Pub Heal. (2019) 29:390–400. doi: 10.1080/09581596.2019.1597965
30. Gryseels C, Bannister-Tyrrell M, Uk S, Set S, Sokha S, Gerrets R, et al. A critical enquiry into variability of insecticidal net use in cambodia: implications for assessing appropriateness of malaria elimination interventions. Am J Trop Med Hyg. (2019) 100:1424–32. doi: 10.4269/ajtmh.18-0730
31. Randall S, Coast E, Antoine P, Compaore N, Dial F-B, Fanghanel A, et al. UN Census “Households” and local interpretations in Africa since independence. SAGE Open. (2015) 52:1–18. doi: 10.1177/2158244015589353
32. Gambia Bureau of Statistics. The Gambia 2013 Population and Housing Census. (2013). Avialable online at: http://www.gbos.gov.gm/ (accessed January 16, 2019).
33. Jasseh M, Gomez P, Greenwood BM, Howie SRC, Scott S, Snell PC, et al. Health & demographic surveillance system profile: Farafenni Health and Demographic Surveillance System in the Gambia. Int J Epidemiol. (2015) 44:837–47. doi: 10.1093/ije/dyv049
34. Berman P, Kendall C, Bhattacharyya K. The household production of health: integrating social science perspectives on micro-level health determinants. Soc Sci Med. (1994) 38:205–15. doi: 10.1016/0277-9536(94)90390-5
35. Hosegood V, Benzler J, Solarsh GC. Population mobility and household dynamics in rural South Africa: implications for demographic and health research. South Afr J Dem. (2005). Avaiable online at: http://www.jstor.com/stable/20853278 (accessed June 23, 2020).
36. Mwesigwa J, Okebe J, Affara M, Di Tanna GL, Nwakanma D, Janha O, et al. On-going malaria transmission in the Gambia despite high coverage of control interventions: a nationwide cross-sectional survey. Malar J. (2015) 14:314. doi: 10.1186/s12936-015-0829-6
37. World Health Organization. World Malaria Report. (2015). Available online at: https://www.who.int/malaria/visual-refresh/en/ (accessed September 15, 2016).
38. Pailthorpe BC. Emergent design. Int Encycl Commun Res Methods. (2017). doi: 10.1002/9781118901731.iecrm0081
39. Lindsay SW, Jawara M, Mwesigwa J, Achan J, Bayoh N, Bradley J, et al. Reduced mosquito survival in metal-roof houses may contribute to a decline in malaria transmission in sub-Saharan Africa. Sci Rep. (2019) 9:7770. doi: 10.1038/s41598-019-43816-0
40. Jatta E, Jawara M, Bradley J, Jeffries D, Kandeh B, Knudsen JB, et al. How house design affects malaria mosquito density, temperature, and relative humidity: an experimental study in rural Gambia. Lancet Planetary Health. (2018) 2:PE498. doi: 10.1016/S2542-5196(18)30234-1
41. Kaindoa EW, Finda M, Kiplagat J, Mkandawile G, Nyoni A, Coetzee M, et al. Housing gaps, mosquitoes and public viewpoints: a mixed methods assessment of relationships between house characteristics, malaria vector biting risk and community perspectives in rural Tanzania. Malar J. (2018) 17:298. doi: 10.1186/s12936-018-2473-4
42. Alaii JA, Van Den Borne HW, Kachur SP, Shelley K, Mwenesi H, Vulule JM, et al. Community reactions to the introduction of permethrin-treated bed nets for malaria control during a randomized controlled trial in Western Kenya. Am J Trop Med Hyg. (2003) 68:128–36. doi: 10.4269/ajtmh.2003.68.128
43. Iwashita H, Dida G, Futami K, Sonye G, Kaneko S, Horio M, et al. Sleeping arrangement and house structure affect bed net use in villages along Lake Victoria. Malar J. (2010) 9:176. doi: 10.1186/1475-2875-9-176
44. Toé LP, Skovmand O, Dabiré KR, Diabaté A, Diallo Y, Guiguemdé TR, et al. Decreased motivation in the use of insecticide-treated nets in a malaria endemic area in Burkina Faso. Malar J. (2009) 8:179. doi: 10.1186/1475-2875-8-175
45. Bledsoe C. Contingent Lives: Fertility, Time, and Aging. Chicago; London: The University of Chicago Press (2002).
46. Gamble D, Salmon LK, Njie AH. People's of the Gambia. (1985). Available online at: https://www.smcm.edu/gambia/wp-content/uploads/sites/31/2015/03/gamble-17.pdf (accessed March, 16, 2016).
47. Madhavan S, Bledsoe CH. The compound as a locus of fertility management: the case of the Gambia. Cult Heal Sex. (2001) 3:451–68. doi: 10.1080/13691050110074219
48. Hausmann Muela S, Muela Ribera J, Toomer E, Peeters Grietens K. The PASS-model: a model for guiding health-seeking behavior and access to care research. Malaria Reports. (2012) 2:3. doi: 10.4081/malaria.2012.e3
49. Janzen JM. Therapy management:concept, reality, process. Med Anthro Quar. (1985) 1:68. doi: 10.1525/maq.1987.1.1.02a00040
50. Carney JA. The bitter harvest of Gambian rice policies. Globalizations. (2008) 5:129–42. doi: 10.1080/14747730802057456
51. Altrogge F, Zanker J. The Political Economy of Migration Governance in the Gambia. Mercat Dialogue Asylum Migr. (2020). Available online at: https://www.researchgate.net/publication/337167520_The_Political_Economy_of_Migration_Governance_in_the_Gambia (accessed July 13, 2019)
52. Swindell K. Migrant groundnut farmers in the Gambia: the persistence of a nineteenth century labor system. Int Migr Rev. (1977) 11:452–72. doi: 10.2307/2545399
53. Cotter C, Sturrock HJW, Hsiang MS, Liu J, Phillips AA, Hwang J, et al. The changing epidemiology of malaria elimination: new strategies for new challenges. Lancet. (2013) 7:382. doi: 10.1016/S0140-6736(13)60310-4
54. Rutherford ME, Dockerty JD, Jasseh M, Howie SRC, Herbison P, Jeffries DJ, et al. Access to health care and mortality of children under 5 years of age in the Gambia: a case-control study. Bull World Health Organ. (2009) 87:216–24. doi: 10.2471/BLT.08.052175
55. Guyer JI. Household and community in African studies. Afr Stud Rev. (1981) 24:87–137. doi: 10.2307/523903
56. Dial NJ, Ceesay SJ, Gosling RD, D'Alessandro U, Baltzell KA. A qualitative study to assess community barriers to malaria mass drug administration trials in the Gambia. Malar J. (2014) 13:47. doi: 10.1186/1475-2875-13-47
57. De Martin S, von Seidlein L, Deen JL, Pinder M, Walraven G, Greenwood B. Community perceptions of a mass administration of an antimalarial drug combination in the Gambia. Trop Med Int Heal. (2001) 6:442–8. doi: 10.1046/j.1365-3156.2001.00723.x
58. Dunn CE, Le Mare A, Makungu C. Malaria risk behaviours, socio-cultural practices and rural livelihoods in southern Tanzania: implications for bednet usage. Soc Sci Med. (2011) 72:408–17. doi: 10.1016/j.socscimed.2010.11.009
59. Alaii JA, Hawley WA, Kolczak MS, Ter Kuile FO, Gimnig JE, Vulule JM, et al. Factors affecting use of permethrin-treated bed nets during a randomized controlled trial in Western Kenya. Am J Trop Med Hyg. (2003) 68:137–41. doi: 10.4269/ajtmh.2003.68.137
60. Monroe A, Moore S, Koenker H, Lynch M, Ricotta E. Measuring and characterizing night time human behaviour as it relates to residual malaria transmission in sub-Saharan Africa: a review of the published literature. Malar J. (2019) 18:6. doi: 10.1186/s12936-019-2638-9
61. Hultin N, Jallow B, Lawrance BN, Sarr A. Autocracy, migration, and the Gambia's “unprecedented” 2016 election. Afr Affairs. (2017) 116:463. doi: 10.1093/afraf/adx007
62. Geissler PW, Kelly A, Imoukhuede B, Pool R. ‘He is now like a brother, I can even give him some blood' – relational ethics and material exchanges in a malaria vaccine ‘trial community' in the Gambia. Soc Sci Med. (2008) 67:596–707. doi: 10.1016/j.socscimed.2008.02.004
63. Kelly AH, Ameh D, Majambere S, Lindsay S, Pinder M. “Like sugar and honey”: the embedded ethics of a larval control project in the Gambia. Soc Sci Med. (2010) 70:12. doi: 10.1016/j.socscimed.2010.02.012
64. Kelly AH. The territory of medical research: experimentation in Africa's smallest state. In: Geissler PW editor. Para-states and Medical Science: Making African Global Health. Duke University Press (2010). p. 302–32.
65. O'Neill S, Dierickx S, Okebe J, Dabira E, Gryseels C, D'Alessandro U, et al. The importance of blood is infinite: conceptions of blood as life force, rumours and fear of trial participation in a Fulani village in rural Gambia. PLoS ONE. (2016) 11:e0160464. doi: 10.1371/journal.pone.0160464
66. Jaiteh F, Dierickx S, Gryseels C, O'Neill S, D'Alessandro U, Scott S, et al. Some anti-malarials are too strong for your body, they will harm you.' Socio-cultural factors influencing pregnant women's adherence to anti-malarial treatment in rural Gambia. Malar J. (2016) 15:195. doi: 10.1186/s12936-016-1255-0
67. Jull J, Giles A, Graham ID. Community-based participatory research and integrated knowledge translation: advancing the co-creation of knowledge. Implement Sci. (2017) 12:150. doi: 10.1186/s13012-017-0696-3
Keywords: malaria elimination, asymptomatic infections, reactive intervention unit, household conceptualization, transdisciplinary research
Citation: Jaiteh F, Ribera JM, Masunaga Y, Okebe J, D'Alessandro U, Balen J, Achan J, Gerrets R and Peeters Grietens K (2021) Complexities in Defining the Unit of Intervention for Reactive Community-Based Malaria Treatment in the Gambia. Front. Public Health 9:601152. doi: 10.3389/fpubh.2021.601152
Received: 31 August 2020; Accepted: 02 February 2021;
Published: 26 February 2021.
Edited by:
Sunil Dhiman, Defence Research & Development Establishment (DRDE), IndiaReviewed by:
Simon Kariuki, Kenya Medical Research Institute (KEMRI), KenyaKim Lindblade, Centers for Disease Control and Prevention (CDC), United States
Copyright © 2021 Jaiteh, Ribera, Masunaga, Okebe, D'Alessandro, Balen, Achan, Gerrets and Peeters Grietens. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Fatou Jaiteh, fjaiteh@mrc.gm